Flexible Statistics and Data Analysis (FSDA) extends MATLAB for a robust analysis of data sets affected by different sources of heterogeneity. It is open source software licensed under the European Union Public Licence (EUPL). FSDA is a joint project by the University of Parma and the Joint Research Centre of the European Commission.

This repository describes a new measure for characterizing self-similarity in high-frequency signals. The introduced method is applied in the context of an important gait data study.

This program classifies elements of some matrices, according to difference of each pair of elements; so that number of classes won't be too many that variance of class members would be invisible, or too few that too different elements would belong to same class.

Repository contains my MATLAB files for the hand-coded MNIST (w/ SGD optimizer) classification model trained for the EEL5813 - Neural Networks: Algorithms and Applications course, PROJECT02

A project for aircraft image feature extraction and classification using the VGG16 model. It includes 20 different military aircraft classes.

🐳 Scripps Whale Acoustics Lab 🌎 Scripps Acoustic Ecology Lab - Triton with remoras in development

Knowledge Is Power is a data analysis and prediction tool leveraging U.S. Census data to provide insights into societal topics. Utilizing machine learning, specifically MATLAB's classification learner, the project predicts educational attainment based on income and offers interactive visualizations of veterans' data.

In this work, an automatic and reproducible methodology is proposed using computer vision techniques for sorting oranges by size and defects. Master thesis written in Spanish.

Letters and numbers classifier for chess games using computer vision and neural networks.

This project will try to detect every type of coin within an image using Computer Vision techniques.

My Matlab Ph.D. thesis coding project: the enhanced version of Tree-like Divide to Simplify (T-DTS) ANN (AI/ML) structure-based tool used for classification tasks. The credits: the v.1.0 was developed by Dr. M. Rybnik under supervision of Prof. K. Madani

CellExplorer is a graphical user interface, a standardized processing module and data structure for exploring and classifying single cells acquired using extracellular electrodes.

The project contains a signal processing pipeline to classify hand written text characters and produce a text string of the handwritten characters

Reconhecimento de Padrões: classificação de sinais elétricos do movimento de uma luva

This is a paper and its supplementary material, bundled together.

Automatic EEG IC classification plugin for EEGLAB

A machine learning approach using Matlab for the automatic classification of sounds.

A machine learning approach to automatic classification of musical genres, implemented using MATLAB

Matlab toolbox to integrate normal (Gaussian) distributions in any dimensions with any parameters in any domain, compute pdf/cdf/inverse cdf of any function of a normal vector, and measures of classification performance among two or more multinormals, like error matrix and d'.

In this paper, we propose two novel time-efficient formulations of the Twin Extreme Learning Machine, which only require the solution of systems of linear equations for obtaining the final classifier. In this sense, they can combine the benefits of the Twin Support Vector Machine and standard Extreme Learning Machine in the true sense.